import intake
import ciofs_hindcast_report as chr
import hvplot.pandas # noqa
import ocean_model_skill_assessor as omsa
import pandas as pd
import cmocean.cm as cmo
USGS BOEM: Single CTD profiles across Cook Inlet#
CTD profiles - USGS BOEM
ctd_profiles_usgs_boem
One-off CTD profiles from 2016 to 2021 in July
USGS Cook Inlet fish and bird survey CTD profiles.
CTD profiles collected in Cook Inlet from 2016-2021 by Mayumi Arimitsu as part of BOEM sponsored research on fish and bird distributions in Cook Inlet. The profiles are collected in July for the years 2016-2021.
The scientific project is described here: https://www.usgs.gov/centers/alaska-science-center/science/cook-inlet-seabird-and-forage-fish-study#overview.
Dataset metadata:
Dataset |
featuretype |
maxLatitude |
maxLongitude |
maxTime |
minLatitude |
minLongitude |
minTime |
|
|---|---|---|---|---|---|---|---|---|
0 |
2016102001 |
profile |
60.2743 |
-152.356 |
2016-07-17 11:16:00 |
60.2743 |
-152.356 |
2016-07-17 11:16:00 |
1 |
2016106001 |
profile |
59.8774 |
-152.579 |
2016-07-18 16:13:00 |
59.8774 |
-152.579 |
2016-07-18 16:13:00 |
2 |
2016120001 |
profile |
60.3062 |
-152.192 |
2016-07-17 08:33:00 |
60.3062 |
-152.192 |
2016-07-17 08:33:00 |
3 |
2016122201 |
profile |
60.1779 |
-151.915 |
2016-07-17 15:56:00 |
60.1779 |
-151.915 |
2016-07-17 15:56:00 |
4 |
2016123001 |
profile |
60.057 |
-152.524 |
2016-07-16 08:12:00 |
60.057 |
-152.524 |
2016-07-16 08:12:00 |
5 |
2016123002 |
profile |
60.1052 |
-152.241 |
2016-07-16 11:11:00 |
60.1052 |
-152.241 |
2016-07-16 11:11:00 |
6 |
2016125001 |
profile |
59.9135 |
-152.194 |
2016-07-14 14:43:00 |
59.9135 |
-152.194 |
2016-07-14 14:43:00 |
7 |
2016126001 |
profile |
59.8026 |
-152.757 |
2016-07-18 19:19:00 |
59.8026 |
-152.757 |
2016-07-18 19:19:00 |
8 |
2016126002 |
profile |
59.8295 |
-152.538 |
2016-07-19 11:15:00 |
59.8295 |
-152.538 |
2016-07-19 11:15:00 |
9 |
2016205701 |
profile |
59.6646 |
-151.233 |
2016-07-23 14:10:00 |
59.6646 |
-151.233 |
2016-07-23 14:10:00 |
10 |
2016206001 |
profile |
59.5644 |
-151.393 |
2016-07-29 10:23:00 |
59.5644 |
-151.393 |
2016-07-29 10:23:00 |
11 |
2016221001 |
profile |
59.6698 |
-151.985 |
2016-07-28 11:22:00 |
59.6698 |
-151.985 |
2016-07-28 11:22:00 |
12 |
2016223001 |
profile |
59.5834 |
-151.446 |
2016-07-24 09:39:00 |
59.5834 |
-151.446 |
2016-07-24 09:39:00 |
13 |
2016223002 |
profile |
59.5713 |
-151.716 |
2016-07-24 12:10:00 |
59.5713 |
-151.716 |
2016-07-24 12:10:00 |
14 |
2016224001 |
profile |
59.5006 |
-151.889 |
2016-07-26 11:25:00 |
59.5006 |
-151.889 |
2016-07-26 11:25:00 |
15 |
2016225001 |
profile |
59.4217 |
-152.025 |
2016-07-26 18:55:00 |
59.4217 |
-152.025 |
2016-07-26 18:55:00 |
16 |
2016226001 |
profile |
59.3211 |
-152.102 |
2016-07-27 10:49:00 |
59.3211 |
-152.102 |
2016-07-27 10:49:00 |
17 |
2017101001 |
profile |
60.358 |
-152.214 |
2017-07-26 08:52:00 |
60.358 |
-152.214 |
2017-07-26 08:52:00 |
18 |
2017103001 |
profile |
60.1284 |
-152.493 |
2017-07-25 09:49:00 |
60.1284 |
-152.493 |
2017-07-25 09:49:00 |
19 |
2017120001 |
profile |
60.3292 |
-152.177 |
2017-07-26 13:12:00 |
60.3292 |
-152.177 |
2017-07-26 13:12:00 |
20 |
2017122001 |
profile |
60.231 |
-152.285 |
2017-07-26 14:38:00 |
60.231 |
-152.285 |
2017-07-26 14:38:00 |
21 |
2017123001 |
profile |
60.0473 |
-152.52 |
2017-07-23 07:29:00 |
60.0473 |
-152.52 |
2017-07-23 07:29:00 |
22 |
2017124001 |
profile |
59.9828 |
-152.263 |
2017-07-27 10:56:00 |
59.9828 |
-152.263 |
2017-07-27 10:56:00 |
23 |
2017125001 |
profile |
59.919 |
-152.27 |
2017-07-22 12:41:00 |
59.919 |
-152.27 |
2017-07-22 12:41:00 |
24 |
2017125002 |
profile |
59.9439 |
-151.941 |
2017-07-22 16:08:00 |
59.9439 |
-151.941 |
2017-07-22 16:08:00 |
25 |
2017201001 |
profile |
59.6637 |
-151.801 |
2017-07-31 11:03:00 |
59.6637 |
-151.801 |
2017-07-31 11:03:00 |
26 |
2017204001 |
profile |
59.6447 |
-151.282 |
2017-07-20 11:57:00 |
59.6447 |
-151.282 |
2017-07-20 11:57:00 |
27 |
2017205001 |
profile |
59.6727 |
-151.197 |
2017-07-19 15:35:00 |
59.6727 |
-151.197 |
2017-07-19 15:35:00 |
28 |
2017206001 |
profile |
59.6599 |
-151.224 |
2017-07-19 11:39:00 |
59.6599 |
-151.224 |
2017-07-19 11:39:00 |
29 |
2017207001 |
profile |
59.5196 |
-151.462 |
2017-07-20 16:40:00 |
59.5196 |
-151.462 |
2017-07-20 16:40:00 |
30 |
2017212001 |
profile |
59.3781 |
-151.891 |
2017-07-28 17:05:00 |
59.3781 |
-151.891 |
2017-07-28 17:05:00 |
31 |
2017214001 |
profile |
59.5773 |
-151.363 |
2017-07-18 15:56:00 |
59.5773 |
-151.363 |
2017-07-18 15:56:00 |
32 |
2017220001 |
profile |
59.7454 |
-151.998 |
2017-07-31 14:42:00 |
59.7454 |
-151.998 |
2017-07-31 14:42:00 |
33 |
2017223001 |
profile |
59.5842 |
-151.512 |
2017-07-30 10:12:00 |
59.5842 |
-151.512 |
2017-07-30 10:12:00 |
34 |
2017224001 |
profile |
59.4971 |
-151.843 |
2017-07-30 17:34:00 |
59.4971 |
-151.843 |
2017-07-30 17:34:00 |
35 |
2017225001 |
profile |
59.3998 |
-152.119 |
2017-07-28 12:41:00 |
59.3998 |
-152.119 |
2017-07-28 12:41:00 |
36 |
2018104001 |
profile |
60.0669 |
-152.537 |
2018-07-14 19:31:00 |
60.0669 |
-152.537 |
2018-07-14 19:31:00 |
37 |
2018120001 |
profile |
60.2993 |
-152.223 |
2018-07-17 11:20:00 |
60.2993 |
-152.223 |
2018-07-17 11:20:00 |
38 |
2018121001 |
profile |
60.2658 |
-152.178 |
2018-07-17 16:39:00 |
60.2658 |
-152.178 |
2018-07-17 16:39:00 |
39 |
2018122001 |
profile |
60.166 |
-152.476 |
2018-07-15 18:53:00 |
60.166 |
-152.476 |
2018-07-15 18:53:00 |
40 |
2018123001 |
profile |
60.0947 |
-151.961 |
2018-07-15 14:06:00 |
60.0947 |
-151.961 |
2018-07-15 14:06:00 |
41 |
2018124001 |
profile |
59.9949 |
-152.297 |
2018-07-18 10:10:00 |
59.9949 |
-152.297 |
2018-07-18 10:10:00 |
42 |
2018125001 |
profile |
59.8945 |
-151.986 |
2018-07-18 14:30:00 |
59.8945 |
-151.986 |
2018-07-18 14:30:00 |
43 |
2018126001 |
profile |
59.8347 |
-152.416 |
2018-07-19 11:23:00 |
59.8347 |
-152.416 |
2018-07-19 11:23:00 |
44 |
2018203001 |
profile |
59.5806 |
-151.52 |
2018-07-12 17:20:00 |
59.5806 |
-151.52 |
2018-07-12 17:20:00 |
45 |
2018203002 |
profile |
59.5905 |
-151.423 |
2018-07-25 09:26:00 |
59.5905 |
-151.423 |
2018-07-25 09:26:00 |
46 |
2018205001 |
profile |
59.6932 |
-151.157 |
2018-07-24 15:53:00 |
59.6932 |
-151.157 |
2018-07-24 15:53:00 |
47 |
2018208001 |
profile |
59.5375 |
-151.518 |
2018-07-13 17:48:00 |
59.5375 |
-151.518 |
2018-07-13 17:48:00 |
48 |
2018214002 |
profile |
59.5746 |
-151.339 |
2018-07-13 11:28:00 |
59.5746 |
-151.339 |
2018-07-13 11:28:00 |
49 |
2018221001 |
profile |
59.6566 |
-151.881 |
2018-07-26 20:01:00 |
59.6566 |
-151.881 |
2018-07-26 20:01:00 |
50 |
2018223001 |
profile |
59.5818 |
-151.473 |
2018-07-23 11:19:00 |
59.5818 |
-151.473 |
2018-07-23 11:19:00 |
51 |
2018223002 |
profile |
59.5737 |
-151.73 |
2018-07-25 16:34:00 |
59.5737 |
-151.73 |
2018-07-25 16:34:00 |
52 |
2018225001 |
profile |
59.4071 |
-152.014 |
2018-07-27 14:49:00 |
59.4071 |
-152.014 |
2018-07-27 14:49:00 |
53 |
2019106001 |
profile |
59.8465 |
-152.807 |
2019-07-21 10:03:00 |
59.8465 |
-152.807 |
2019-07-21 10:03:00 |
54 |
2019121001 |
profile |
60.1817 |
-152.209 |
2019-07-19 09:35:00 |
60.1817 |
-152.209 |
2019-07-19 09:35:00 |
55 |
2019122001 |
profile |
60.1561 |
-152.379 |
2019-07-19 11:59:00 |
60.1561 |
-152.379 |
2019-07-19 11:59:00 |
56 |
2019123001 |
profile |
60.0269 |
-151.982 |
2019-07-19 13:32:00 |
60.0269 |
-151.982 |
2019-07-19 13:32:00 |
57 |
2019125001 |
profile |
59.928 |
-152.179 |
2019-07-17 12:43:00 |
59.928 |
-152.179 |
2019-07-17 12:43:00 |
58 |
2019126001 |
profile |
59.8979 |
-151.898 |
2019-07-21 17:38:00 |
59.8979 |
-151.898 |
2019-07-21 17:38:00 |
59 |
2019205001 |
profile |
59.6756 |
-151.205 |
2019-07-28 11:24:00 |
59.6756 |
-151.205 |
2019-07-28 11:24:00 |
60 |
2019210001 |
profile |
59.4996 |
-151.735 |
2019-07-26 12:20:00 |
59.4996 |
-151.735 |
2019-07-26 12:20:00 |
61 |
2019221001 |
profile |
59.6465 |
-152.216 |
2019-07-22 13:47:00 |
59.6465 |
-152.216 |
2019-07-22 13:47:00 |
62 |
2019223001 |
profile |
59.5795 |
-151.4 |
2019-07-24 13:01:00 |
59.5795 |
-151.4 |
2019-07-24 13:01:00 |
63 |
2019223002 |
profile |
59.5726 |
-151.765 |
2019-07-27 16:45:00 |
59.5726 |
-151.765 |
2019-07-27 16:45:00 |
64 |
2019226001 |
profile |
59.3545 |
-152.231 |
2019-07-27 11:06:00 |
59.3545 |
-152.231 |
2019-07-27 11:06:00 |
65 |
2021105001 |
profile |
60.0328 |
-152.547 |
2021-07-18 17:37:00 |
60.0328 |
-152.547 |
2021-07-18 17:37:00 |
66 |
2021122001 |
profile |
60.1651 |
-152.314 |
2021-07-20 15:17:00 |
60.1651 |
-152.314 |
2021-07-20 15:17:00 |
67 |
2021123001 |
profile |
60.0727 |
-152.062 |
2021-07-21 16:40:00 |
60.0727 |
-152.062 |
2021-07-21 16:40:00 |
68 |
2021124001 |
profile |
60.0058 |
-152.25 |
2021-07-21 11:20:00 |
60.0058 |
-152.25 |
2021-07-21 11:20:00 |
69 |
2021125001 |
profile |
59.8989 |
-151.97 |
2021-07-18 10:13:00 |
59.8989 |
-151.97 |
2021-07-18 10:13:00 |
70 |
2021126001 |
profile |
59.8513 |
-152.565 |
2021-07-23 10:20:00 |
59.8513 |
-152.565 |
2021-07-23 10:20:00 |
71 |
2021205001 |
profile |
59.7194 |
-151.104 |
2021-07-25 09:01:00 |
59.7194 |
-151.104 |
2021-07-25 09:01:00 |
72 |
2021210001 |
profile |
59.5051 |
-151.586 |
2021-07-27 19:09:00 |
59.5051 |
-151.586 |
2021-07-27 19:09:00 |
73 |
2021221001 |
profile |
59.667 |
-152.202 |
2021-07-30 15:41:00 |
59.667 |
-152.202 |
2021-07-30 15:41:00 |
74 |
2021223001 |
profile |
59.582 |
-151.579 |
2021-07-29 11:48:00 |
59.582 |
-151.579 |
2021-07-29 11:48:00 |
75 |
2021223002 |
profile |
59.5683 |
-151.419 |
2021-07-29 17:10:00 |
59.5683 |
-151.419 |
2021-07-29 17:10:00 |
76 |
2021224001 |
profile |
59.4972 |
-152.164 |
2021-07-26 14:43:00 |
59.4972 |
-152.164 |
2021-07-26 14:43:00 |
77 |
2021226001 |
profile |
59.3349 |
-152.047 |
2021-07-27 12:25:00 |
59.3349 |
-152.047 |
2021-07-27 12:25:00 |
cat = intake.open_catalog(chr.CAT_NAME("ctd_profiles_usgs_boem"))
Map of CTD Profiles#
getattr(chr.src.plot_dataset_on_map, "ctd_profiles_usgs_boem")("ctd_profiles_usgs_boem")
2016#
2016102001
cat['2016102001'].plot.data()
2016106001
cat['2016106001'].plot.data()
2016120001
cat['2016120001'].plot.data()
2016122201
cat['2016122201'].plot.data()
2016123001
cat['2016123001'].plot.data()
2016123002
cat['2016123002'].plot.data()
2016125001
cat['2016125001'].plot.data()
2016126001
cat['2016126001'].plot.data()
2016126002
cat['2016126002'].plot.data()
2016205701
cat['2016205701'].plot.data()
2016206001
cat['2016206001'].plot.data()
2016221001
cat['2016221001'].plot.data()
2016223001
cat['2016223001'].plot.data()
2016223002
cat['2016223002'].plot.data()
2016224001
cat['2016224001'].plot.data()
2016225001
cat['2016225001'].plot.data()
2016226001
cat['2016226001'].plot.data()
2017#
2017101001
cat['2017101001'].plot.data()
2017103001
cat['2017103001'].plot.data()
2017120001
cat['2017120001'].plot.data()
2017122001
cat['2017122001'].plot.data()
2017123001
cat['2017123001'].plot.data()
2017124001
cat['2017124001'].plot.data()
2017125001
cat['2017125001'].plot.data()
2017125002
cat['2017125002'].plot.data()
2017201001
cat['2017201001'].plot.data()
2017204001
cat['2017204001'].plot.data()
2017205001
cat['2017205001'].plot.data()
2017206001
cat['2017206001'].plot.data()
2017207001
cat['2017207001'].plot.data()
2017212001
cat['2017212001'].plot.data()
2017214001
cat['2017214001'].plot.data()
2017220001
cat['2017220001'].plot.data()
2017223001
cat['2017223001'].plot.data()
2017224001
cat['2017224001'].plot.data()
2017225001
cat['2017225001'].plot.data()
2018#
2018104001
cat['2018104001'].plot.data()
2018120001
cat['2018120001'].plot.data()
2018121001
cat['2018121001'].plot.data()
2018122001
cat['2018122001'].plot.data()
2018123001
cat['2018123001'].plot.data()
2018124001
cat['2018124001'].plot.data()
2018125001
cat['2018125001'].plot.data()
2018126001
cat['2018126001'].plot.data()
2018203001
cat['2018203001'].plot.data()
2018203002
cat['2018203002'].plot.data()
2018205001
cat['2018205001'].plot.data()
2018208001
cat['2018208001'].plot.data()
2018214002
cat['2018214002'].plot.data()
2018221001
cat['2018221001'].plot.data()
2018223001
cat['2018223001'].plot.data()
2018223002
cat['2018223002'].plot.data()
2018225001
cat['2018225001'].plot.data()
2019#
2019106001
cat['2019106001'].plot.data()
2019121001
cat['2019121001'].plot.data()
2019122001
cat['2019122001'].plot.data()
2019123001
cat['2019123001'].plot.data()
2019125001
cat['2019125001'].plot.data()
2019126001
cat['2019126001'].plot.data()
2019205001
cat['2019205001'].plot.data()
2019210001
cat['2019210001'].plot.data()
2019221001
cat['2019221001'].plot.data()
2019223001
cat['2019223001'].plot.data()
2019223002
cat['2019223002'].plot.data()
2019226001
cat['2019226001'].plot.data()
2021#
2021105001
cat['2021105001'].plot.data()
2021122001
cat['2021122001'].plot.data()
2021123001
cat['2021123001'].plot.data()
2021124001
cat['2021124001'].plot.data()
2021125001
cat['2021125001'].plot.data()
2021126001
cat['2021126001'].plot.data()
2021205001
cat['2021205001'].plot.data()
2021210001
cat['2021210001'].plot.data()
2021221001
cat['2021221001'].plot.data()
2021223001
cat['2021223001'].plot.data()
2021223002
cat['2021223002'].plot.data()
2021224001
cat['2021224001'].plot.data()
2021226001
cat['2021226001'].plot.data()